Crack Java 8 Stream API interview questions with 20 hands-on coding problems solved live in IntelliJ!
This is your one-stop guide for Stream API interview prep — from filter/map/reduce to parallel streams & collectors.
In this video, I walk you through 20 must-know Java 8 Stream API interview questions — each explained with a live hands-on coding demo in IntelliJ IDEA. Whether you're preparing for product-based companies or service-based interviews, these problems cover everything interviewers actually ask.
🔥 What You'll Learn:
1. Filter(), map(), sort() & distinct operations on lists
2. Finding 2nd highest salary & longest string using streams
3. Partitioning even/odd numbers with Collectors.partitioningBy()
4. Grouping employees by department using Collectors.groupingBy()
5. Flattening nested lists with flatMap()
6. Using reduce() for aggregation
7. Finding common elements between two lists
8. Average salary & max salary per department
9. Converting a list to a comma-separated string with Collectors.joining()
10. Parallel streams — performance gains & concurrency pitfalls with ArrayList
📌 Questions Covered:
Q1. Remove duplicates & sort in descending order
Q2. Filter odd numbers & square them
Q3. Find the 2nd and 3rd elements
Q4. Partition a list into even and odd
Q5. Find the employee with the highest salary
Q6. Group words by their length
Q7. Count word frequency in a list
Q8. Flatten a list of lists
Q9. Find the total salary by department
Q10. Get the top 3 highest-paid employees
Q11. Count how many employees are in each department
Q12. Find total transaction amount per category
Q13. Find the average salary of employees in each department
Q14. Find the highest paid employee in each department
Q15. Convert a list of employee names into a comma-separated string
Q16. Find common elements between two lists
Q17. Flatten a list of lists & remove duplicates
Q18. Print all employee names as fast as possible (parallel streams)
Q19. Spot the bug — what is wrong with this code?
Q20. Compute total salary of all employees as fast as possible
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